Exploring the Genetic Landscape of Metabolic Phenotypes with MetaboSignal. Issue 1 (9th April 2018)

• Record Type: Journal Article
• Authors: Rodriguez‐Martinez, Andrea; Ayala, Rafael; Posma, Joram M.; Dumas, Marc‐Emmanuel
• Editors: Baxevanis, Andreas D.; Petsko, Gregory A.; Stein, Lincoln D.; Stormo, Gary D.
• Is Part Of: Current protocols in bioinformatics. Volume 61:Issue 1(2018)
• Page Start: 14.14.1
• Page End: 14.14.13
• Publication Date: 2018-04-09
• Subjects: genomics -- metabonomics -- network‐analysis -- R/Bioconductor -- systems‐biology; Bioinformatics -- Laboratory manuals; Nucleotide sequence -- Laboratory manuals; Amino acid sequence -- Laboratory manuals; Base Sequence; Amino Acid Sequence; Computational Biology -- methods; Databases, Genetic; Proteins -- analysis; Sequence Analysis -- methods; Sequence Homology; Amino acid sequence; Bioinformatics; Nucleotide sequence; Laboratory Manuals; Laboratory manuals; 570.285
• DOI: 10.1002/cpbi.41
• Languages: English
• ISSNs: 1934-3396

Abstract

Abstract: MetaboSignal is an R/Bioconductor package designed to explore the relationships between genes and metabolites, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) as its primary database. It is a network‐based approach that allows overlaying metabolic and signaling pathways and exploring the topological relationship between genes (signaling or metabolic genes) and metabolites. MetaboSignal is ideally suited to identify candidate genes in metabolome genome‐wide association studies (mGWAS), particularly in the case of trans ‐acting associations. It can also be used to provide mechanistic explanations of perturbed metabolic patterns observed in genetic models, as well as to identify novel target metabolic pathways of signaling genes. © 2018 by John Wiley & Sons, Inc.